Title

Author

Thesis Defended

Spring 2012

Document Type

Thesis

Department

Environmental Studies

First Advisor

Dale Miller

Second Advisor

Andrew Martin

Third Advisor

Yuri Springer

Abstract

Climate change has been observed to be affecting the patterns of infectious diseases around the world (Tokarevich et al, 2011; Scharlemann et al. 2008). One of the primary climate-associated mechanisms of change for disease vectors is the expansion or contraction of their geographical ranges. The goal of this thesis was to investigate the relationship between climate change and the distribution of insect vectors by modeling the distribution of the Lone Star tick (Amblyomma americanum). The Lone Star tick is endemic to the eastern United States and has been expanding its range from the southeastern United States to more northern latitudes (Cooley and Kohls, 1944; Good, 1972, Mixson etal, 2006). The tick transmits several pathogens that can cause diseases in humans including human monocytotropic ehrilichiosis, and is a public health concern. The methods for this research were to take the current distribution of the tick (based on distribution information compiled from published scientific literature, Veterinary Services laboratories of the USDA, and the US National tick collection), and build a statistical niche model with 18 climate datasets using maximum Entropy (MaxEnt) statistical software. The climate data were obtained from WorldClim database, who acquired their data from Global Historical Climatology Network, the FAO, the WMO, the International Center for Tropical Agriculture (CIAT)/ Once the tick’s current niche model (based on climate) had been constructed it was projected into a future using eight different future climate scenarios. The results and future distribution maps suggest a high probability for range expansion of the tick to higher latitudes and to western United States. In addition, the models with the most extreme warming scenarios predicted relatively lower probability for range expansion of the tick in comparison to models that had more moderate global warming scenarios. The climate variables that were most significant in determining the niche of the tick were extreme temperature and precipitation parameters, possibly showing that tick distribution is limited by temperature and precipitation maximum and minimums.